Multi-comp. CA1 O-LM interneuron model with varying dendritic Ih distributions (Sekulic et al 2015)

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Accession:182797
The model presented here was used to investigate possible dendritic distributions of the HCN channel-mediated current (Ih) in models of oriens-lacunosum/moleculare (O-LM) CA1 hippocampal interneurons. Physiological effects of varying the dendritic distributions consisted of examining back-propagating action potential speeds.
Reference:
1 . Sekulic V, Chen TC, Lawrence JJ, Skinner FK (2015) Dendritic distributions of I h channels in experimentally-derived multi-compartment models of oriens-lacunosum/moleculare (O-LM) hippocampal interneurons. Front Synaptic Neurosci 7:2 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA1 stratum oriens lacunosum-moleculare interneuron ;
Channel(s): I Na,t; I A; I K; I K,leak; I M; I h; I K,Ca; I Calcium; I_AHP;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Active Dendrites; Detailed Neuronal Models; Conductance distributions;
Implementer(s):
Search NeuronDB for information about:  I Na,t; I A; I K; I K,leak; I M; I h; I K,Ca; I Calcium; I_AHP;
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SekulicEtAl2015
04525047--90nA
04610022--90nA
README.html
cad.mod *
ICaL.mod *
ICaT.mod *
Ih.mod
IKa.mod *
IKCa.mod *
Ikdrf.mod *
Ikdrfaxon.mod *
Ikdrs.mod *
Ikdrsaxon.mod *
Ikleakaxon.mod *
Ikleaksd.mod *
IMminret.mod *
IMmintau.mod *
Ipassaxon.mod *
Ipasssd.mod *
Naaxon.mod *
Nadend.mod *
Nasoma.mod *
.initactivesdRichy.hoc.swp
.ipsc-cihr.hoc.swp
active_mods.hoc
celltestt.dat
dendIh_funcs.hoc
frontiers_Fig10.hoc
ihold_funcs.hoc
init_d_lambda_Richy_trunc.hoc
init_d_lambda_Starfish_full.hoc
init_exp.hoc
init_Richy_RN.hoc
initactivesdRichy.hoc
initactivesdStarfish.hoc
initactivesdStarfishfull.hoc
iprotocol.hoc
ipsc.hoc
ipsc-cihr.hoc
mosinit.hoc
nsegfuncs.hoc
param_active_cond.hoc
params.hoc
Richytrunctest2.hoc
rn.hoc
screen.png
screen1.png
Starfishfull.hoc
Starfishtrunc.hoc
startup_R3.sh
startup_R4.sh
startup_S3.sh
startup_S4.sh
                            
load_file("read_param.hoc")

// adjustable parameter
strdef param_file
param_file = "/Users/vsekulic/research/summer2011/d_lambda_val.dat"

/////////////////////////
// DO NOT MODIFY BELOW //
/////////////////////////

// first get our value for d_lambda
//d_lambda = read_params(param_file, 1)
d_lambda = read_param(param_file)

// define path for file
strdef TOPDIR, DATFILE, fullpath
TOPDIR = "/Users/vsekulic/research/summer2011/2006-RichyandStarfish/vectorfiles/"
DATFILE = "richy_trunc_d_lambda_"
sprint(fullpath, "%s/%s%g.dat", TOPDIR, DATFILE, d_lambda)

load_file("initactivesdRichy.hoc")

soma area(.5)
forsec all { nseg = int((L/(d_lambda*lambda_f(100))+.9)/2)*2 + 1  }
totnseg = 0
forsec all { totnseg = totnseg + nseg }

// setup vectors for t and V data
objref rect, recv_soma, recv_dend, recv_axon
rect = new Vector()
recv_soma = new Vector()
recv_dend = new Vector()
recv_axon = new Vector()

rect.record(&t, 0.025)
recv_soma.record(&soma[0].v(0.5), 0.025)
recv_dend.record(&dendrite[43].v(0.5), 0.025)
recv_axon.record(&axon[196].v(0.166667), 0.025)

// run simulation
tstop=200
run()

// open file for saving 
objref savdata
savdata = new File()
savdata.wopen(fullpath)
savdata.printf("%d\n", totnseg)
//savdata.printf("t soma[0].v(0.5) dendrite[43].v(0.5) axon[196].v(0.166667)\n")

// assemble matrix with data for efficiency & write it to file
objref M
M = new Matrix()
M.resize(recv_soma.size(),4)
M.setcol(0, rect)
M.setcol(1, recv_soma)
M.setcol(2, recv_dend)
M.setcol(3, recv_axon)
M.fprint(0, savdata, " %g")
savdata.close()

quit()